Passivity and Dissipativity of Fractional-Order Quaternion-Valued Fuzzy Memristive Neural Networks: Nonlinear Scalarization Approach

被引:38
|
作者
Li, Ruoxia [1 ]
Cao, Jinde [2 ]
机构
[1] Shaanxi Normal Univ, Sch Math & Informat Sci, Xian 710062, Peoples R China
[2] Southeast Univ, Sch Math, Nanjing 211189, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Biological neural networks; Quaternions; Neurons; Fuzzy logic; Cybernetics; Mathematical model; Memristors; Dissipativity; fractional order; nonlinear scalarization; passivity; quaternion valued; SYNCHRONIZATION; DISCRETE;
D O I
10.1109/TCYB.2020.3025439
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, the problem of passivity and dissipativity analysis is investigated for a class of fractional-order quaternion-valued fuzzy memristive neural networks. Based on the famous nonlinear scalarizing function, a nonlinear scalarization method is developed, which can be employed to compare the "size" of two different quaternions. In this way, the convex closure proposed by the quaternion-valued connection weights is meaningful. By constructing proper Lyapunov functional, several improved passivity criteria and dissipativity conclusions are established, which can be checked efficiently by utilizing some standard mathematical calculations. Finally, the obtained results are validated by simulation examples.
引用
收藏
页码:2821 / 2832
页数:12
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